AI / Analytics Engineer

About the role

We are seeking an experienced AI / Analytics Engineer to join Carrier’s Global Data, Analytics & AI organization. This role is ideal for a hands-on engineer who combines a strong analytics foundation with modern AI/ML, GenAI, and Agentic AI engineering experience to develop scalable, business-critical solutions.

The AI / Analytics Engineer will work closely with business stakeholders, product managers, and platform teams to understand business problems, translate them into data- and AI-driven solutions, and deliver production-ready capabilities that create measurable business value. This role requires an entrepreneurial mindset, the ability to move quickly from idea to solution, and a strong focus on building solutions that scale across functions, regions, and use cases.

Key Responsibilities

AI / Analytics Engineer will be responsible for:

• Design, develop, and deploy analytics, AI/ML, GenAI, and Agentic AI solutions that address real business problems across functions such as Supply Chain, Manufacturing, Service, Marketing, and Commercial Operations.

• Build and maintain analytics engineering pipelines (data ingestion, transformation, semantic layers, feature engineering) to support advanced analytics and AI use cases.

• Develop and operationalize machine learning models (predictive, prescriptive, optimization) and GenAI solutions (e.g., RAG-based assistants, summarization, Q&A, copilots).

• Design and implement Agentic AI workflows that orchestrate tools, data, and models to automate multi-step business processes with appropriate guardrails and human-in-the-loop controls.

Business Understanding & Problem Solving

• Partner with business stakeholders and product teams to understand requirements, frame problems, and identify opportunities where analytics and AI can drive impact.

• Translate ambiguous business needs into clear technical designs, data requirements, and solution architectures.

• Apply strong analytical thinking to define success metrics, validate assumptions, and continuously improve solutions based on outcomes.

Platform, Scale & Operations

• Collaborate with data platform, architecture, and security teams to ensure solutions align with enterprise standards, governance, and scalability requirements.

• Optimize models and pipelines for performance, reliability, cost, and scalability.

• Support production deployment and monitoring of analytics and AI solutions, including model performance, data quality, and system reliability.

• Contribute to best practices for MLOps / LLMOps, including versioning, testing, evaluation, and monitoring.

Innovation & Continuous Improvement

• Stay current with emerging trends in AI/ML, GenAI, Agentic AI, and analytics engineering, and proactively evaluate how new technologies can be applied at Carrier.

• Experiment, prototype, and iterate quickly—while designing solutions that can be scaled and reused across the enterprise.

• Promote responsible and ethical AI practices, including bias mitigation, transparency, and regulatory compliance.

• Bachelor’s degree in Computer Science, Data Science, Engineering, Business Analytics, or a related field.

• 3-5 years of relevant experience in analytics engineering, data engineering, AI/ML engineering, or advanced analytics roles.

• Strong experience working with data analytics, data modeling, and large datasets in enterprise environments.

• Hands-on experience developing and deploying AI/ML models and analytics solutions.

• Proficiency in Python, SQL, and modern analytics or ML frameworks.

• Experience collaborating with business stakeholders and cross-functional teams.

• Hands-on experience with GenAI (e.g., RAG architectures, prompt engineering, LLM integration, evaluation frameworks).

• Exposure to or experience building Agentic AI solutions (tool-using agents, workflow orchestration, automation).

• Experience with modern data and analytics platforms such as Snowflake, Databricks, and visualization tools like Power BI.

• Familiarity with cloud platforms (AWS, Azure, or GCP).

• Experience applying Agile / product-oriented delivery models.

• Background in manufacturing, industrial, or HVAC domains is a plus.

Carrier is An Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class.

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